This guide provides a step-by-step guide to 1) convert BAM files (i.e., public) to paired-end FASTQ files; and 2) run the nextflow nf-core/sarek variant calling pipeline.
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Conda installation: https://docs.conda.io/projects/conda/en/latest/user-guide/install/linux.html
Code Block wget https://repo.anaconda.com/miniconda/Miniconda3-py37_22.11.1-1-Linux-x86_64.sh bash Miniconda3-py37_22.11.1-1-Linux-x86_64.sh
nextflow installation: Nextflow
Create a Conda environment with tools needed for downstream analyses
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To install several tools, prepare a file called environment.yml (example below). Tip: use a text editor (i.e., vim, nano, or other) to copy and paste the code below into the file.
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Move to the folder where all the BAM files are present and prepare the following script (i.e.,launch_BAM2FASTQ.pbs):
| Code Block |
|---|
#!/bin/bash -l
#PBS -N BAM2FASTQ
#PBS -l walltime=24:00:00
#PBS -l mem=8gb
#PBS -l ncpus=4
cd $PBS_O_WORKDIR
#activate the conda environment with the necessary tools
conda activate liver
#Sort reads in BAM file by indentifier-name (-n) using 4 CPUs (-@ 4). Note 'prefix' for sorted file noted after $i (input BAM file)
for i in `ls --color=never *.bam`
do
echo $i
samtools sort -@ 4 -n $i ${i%%.bam}_sorted
done
#Extract paired end reads in FASTQ format
for file in `ls --color=never *sorted.bam`
do
echo $file
bedtools bamtofastq -i $file -fq ${file%%.bam}_R1.fastq -fq2 ${file%%.bam}_R2.fastq
#compress FASTQ files to run using the sarek pipeline
gzip -c -9 ${file%%.bam}_R1.fastq > ${file%%.bam}_R1.fastq.gz
gzip -c -9 ${file%%.bam}_R1.fastq > ${file%%.bam}_R2.fastq.gz
done |
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To run Sarek 3 files are required:
launch.pbs → details on how to run the workflow
~/.nextflow/config → specify how to run the workflow in the HPC
samplesheet.csv → provides information on the samples and data to be used (i.e., FASTQ, BAM or CRAM)
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PHASE I - preprocessing
Below is an example of a launch_phase1.pbs file for mapping onto the selected genome:
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| Code Block |
|---|
singularity {
cacheDir = '$HOME/NXF_SINGULARITY_CACHEDIR'
autoMounts = true
}
conda {
cacheDir = '$HOME/NXF_CONDA_CACHEDIR'
}
singularity {
enabled = true
autoMounts = true
}
process {
executor = 'pbspro'
beforeScript = {
"""
source $HOME/.bashrc
source $HOME/.profile
"""
}
scratch = false
cleanup = false
} |
Example of a samplesheet.csv file:
| Code Block |
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patient,sample,lane,fastq_1,fastq_2 healthy_11,1,1,/path/to/data/1.Healthy/Healthy_Combined_11_sorted_R1.fastq.gz,/path/to/data/1.Healthy/Healthy_Combined_11_sorted_R2.fastq.gz |
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Prepare/edit the following launch_phase2.pbs script:
| Code Block |
|---|
#!/bin/bash -l
#PBS -N sarek_II
#PBS -l walltime=48:00:00
#PBS -l select=1:ncpus=1:mem=5gb
cd $PBS_O_WORKDIR
NXF_OPTS='-Xms1g -Xmx4g'
module load java
#run the sarek pipeline
nextflow run nf-core/sarek \
-r 3.1.1 \
-profile singularity \
--genome GATK.GRCh38 \
--step variant_calling \
--tools haplotypecaller \
--wes \
-resume |
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Prepare/edit the following launch_phase3.pbs script:
| Code Block |
|---|
#!/bin/bash -l
#PBS -N sarek_III
#PBS -l walltime=48:00:00
#PBS -l select=1:ncpus=1:mem=5gb
cd $PBS_O_WORKDIR
NXF_OPTS='-Xms1g -Xmx4g'
module load java
#run the sarek pipeline
nextflow run nf-core/sarek \
-r 3.1.1 \
-profile singularity \
--genome GATK.GRCh38 \
--step annotate \
--tools vep,snpeff \
--wes \
-resume |
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